4 INHERITANCE STUDY OF AGRONOMICAL TRAITS OF RICE UNDER STAGNANT FLOODING AND NORMAL
CONDITION
Abstract
Information of genetic model related to stagnant flooding tolerance is essential in the utilization of rice germplasm for improving the effectiveness of
breeding program. This study aimed to elucidate genetic control and heritability of agronomic traits under stagnant flooding stress and normal conditions. The rice
genotype IRRI 119 was used as a tolerant parent and IR 42 as a sensitive parent. The materials used were six population which were obtained from crossing of the
genotypes. The materials were grown at the stagnant flooding stress and normal spot. The experiment was conducted at the Experimental Station of Indonesian
Center for Rice Research in the wet season of December 2015 to April 2016. The grain yield and yield components did not fit to additive-dominant model, which
indicating the presence of non-allelic interaction. Joint scaling test with six parameter revealed duplicate and complementary epistasis fitted to explain gene
action model. The heritability estimates under stress condition were lower compared to the ones in the controlled condition. The strategy for breeding program
to improving grain yield under stagnant flooding stress is delaying the selection after several generations until high level of gene fixation was attained. Additionally,
it could be useful to conduct shuttle breeding between stress and controlled environment.
Key words: generation mean analysis, joint scaling test, stagnant flooding, rice
4.1 Introduction
Rice is often the only cereal that can be grown in flood-prone ecosystem. Rice fields in these flood-prone areas are subject to either transient flash floods
leading to total submergence or to long-term partial floods stagnant flooding, SF, and both often occur in the same field within one cropping season Mackill et al.
1996. Stagnant flooding prolonged partial flooding; medium deep occurs in areas when floodwater of 25
–50 cm stagnates in the field from a few weeks to several months.
Rice varieties respond to the slowly rising water of stagnant flooding by elongating their stems or leaves escape. Internode elongation keeps the top leaves
above the water surface, thereby facilitating respiration. Moderate shoot elongation rate strongly and positively correlated with grain yield under stagnant flooding.
However, elongation at rates of 2.0 cm day
-1
was associated with reduced harvest index due to a smaller panicle size and the increased lodging. Tolerant varieties
should be inherently tall or elongate moderately along with the rising of the water. Improvement of stagnant flooding tolerant should involve combination of both of
these traits to develop an appropriate phenotype Kato et al. 2014.
The improvement of tolerance to abiotic stress has been a major goal in many breeding projects; however, there is no unanimous opinion regarding the best
strategy to deploy and which traits to target Blum 1988. The slow progress
obtained through conventional approaches is largely due to 1 poor knowledge of the genetic and physiological basis of the factors imparting tolerance to abiotic
stresses and 2 the low heritability of yield and its components under unfavorable conditions Ceccarelli and Grando 1996.
Various genetic studies reported the monogenic, recessive Eiguchi et al. 1993, monogenic, dominant Tripathi and Balakrishana Rao 1985, and polygenic
control of the deep-water trait in rice Hamamura and Kuplanchankul 1979, Morishima et al. 1962. However, these reports were not consistent. Inheritance of
elongation ability and its related phenotypes in rice is complex, and results based on earlier studies have varied considerably depending largely on the parental lines
used. Segregation of rice plants with respect to their responses to different flooding stress conditions was largely due to the differential expression of elongation and
submergence tolerance genes.
The success of selection in cross population depend on the knowledge of inheritance pattern pf the desired traits. The main purpose of rice breeding tolerant
stagnant flooding stress is to increase grain yield, however, yield is a quantitative trait and is affected by many genes and non-genetic factors. To increase yield under
stagnant flooding stress, it is necessary to improve agronomical traits affect grain yield. Therefore, it is necessary information of inheritance pattern of these traits
Singh et al. 1986.
Information about gene effect including mean m, additive d and dominant gene effects h, and three types of non-allelic gene interactions, that are
additive x additive i, additive x dominant j, and dominant x dominant l are very important. Generation mean analysis is a simple and useful method for estimating
gene effects of polygenic traits, and nature of epistasis is helpful in deciding breeding program to be adopted for the improvement of quantitative traits Singh
and Singh 1992.
The study aims to acquire information of genetic control and heritability of agronomical traits under stagnant flooding stress. Information of genetic control
would be useful for determining appropriate selection method in developing new varieties tolerant to long-term stagnant flooding stress.
4.2 Materials and Methods 4.2.1 Plant materials
The rice genotype IR 119 were used as tolerant parent, while IRRI 42 as sensitive parent. IRRI 119 was considered to be stagnant flooding tolerant in rice
breeding program at IRRI Collard et al. 2013; Nugraha et al. 2013; Kato et al. 2014; and Vergara et al. 2014. IR 42 is determined as stagnant flooding susceptible
based on Chapter 3 and also supported by Vergara et al. 2014 and Yullianida et al. 2015. The genotypes were crossed to generate F
1
, F
2
, BCP
1
, and BCP
2
populations. The experiment was conducted in the Experimental Station of Indonesian Center for Rice Research in wet season of September 2015 to February
2016.
4.2.2 Design of field trial
Two plots were used for stagnant flooding site and normal site. For stagnant flooding site, the materials were grown inside the pond with gradual flooding
treatment. For the control site, the materials were grown in the rice field with shallow flooding.
The materials grown were P
1
, P
2
, F1, F
2
, BCP
1
, and BCP
2
. The number population used in each site were 40 plants of the parents and 50 plants of the F
1
; 60 of BCP
1
and BCP
2
; and 320 of F
2
population. The materials were grown with the arrangement of 25 cm x 25 cm of spacing.
In the stagnant flooding site, the plants were situated at the 2-3 cm of water depth from 0 to 7 days after transplanting DAT. The water then were increased
twice a week at a rate of 1.43 cm day
-1
during early vegetative stage from 7 to 21 DAT; and three times a week at a rate of 2.14 cm day
-1
during the late vegetative stage from 21 to 35 DAT. Then, a water depth of 50
– 80 cm will be maintained from 35 DAT until maturity Kato et. al 2014, modified. The gradual increase in
water depth is typical of the long-term stagnant floods in some areas of tropical Asia Singh et al. 2011.
Response of population to stagnant flooding stresses was evaluated based on agronomic traits. The observed traits were plant height, number of productive
tiller, weight of 100 grain, flowering date, length of panicle, and grain yield per plant. Grain yield per plant of P1, P2, and F1 was estimated by calculating grain
yield per plot were corrected with number of productive tillers per hills on all of members of each P1, P2, and F1.
4.2.3 Statistical analysis 4.2.3.1 Generation mean analysis
There are six genetic components on a completely di-genic model; they are mean m, effect of additive gene d, and effect of dominant gene h, interaction
of additive x additive number i, interaction of additive x dominant number j, and interaction of dominant x dominant number l Singh and Chaudary 1979. Genetic
model testing is combination of six genetic components so that there are eight models to be tested. Eight models include of 1 two genetic components model
m[d]; 2 three genetic components model m[d] [h] as additive dominant model; 3 four genetic component model m[d] [h] [i], m[d] [h] [j], m[d] [h] [l], and
4 five genetic components model m[d] [h] [i] [j] , m[d] [h] [i] [l] , and m[d] [h] [j] [l] .
First step for genetic model testing is scaling test. Scaling test estimate gene action and model genetic by testing several generation separately. Scaling test used
three-parameter A=2B
1
– P
1
– F
1
, B = 2B
2
– P
2
– F
1
, C = 4F
2
– 2 F
1
– P
1
– P
2
to explain conformity of additive dominant. If scaling test is not significantly different
t t
table 0.05;~
= 1.96, it identified that the gene action is additive dominant. If scaling test showed any significant different, the gene action is inter-allelic or
epistasis. Joint scaling test is used to obtain appropriate interaction model. Joint scaling test estimate gene action and model genetic by testing several generation
simultaneously. It is allow to estimate genetic model fit test. Six-parameter used in joint scaling test that are m = ½ P
1
+ ½ P
2
+ 4F
2
– 2B
1
– 2B
2
; d = 6B
1
+ 6B
2
– 8F
2
- F
1
– 1 ½ P
1
– 1 ½ P
2
; aa = 2B
1
+ 2B
2
– 4F
2
; ad = 2B
1
– P
1
– 2B
2
+ P
2
; dd = P
1
+ P
2
+ 2F
1
+ 4F
2
– 4B
1
– 4B
2
. Appropriate genetic model is determined based on X
2
X
2tabel α = 0.05; db = n-3
, with n is number of generation. Mather and Jink 1982. Heritability estimation can be obtained by the formula of Roy 2000 with
calculation of additive variance D, dominant variance H, and environment
